fwildclusterboot - Fast Wild Cluster Bootstrap Inference for Linear Models
Implementation of fast algorithms for wild cluster bootstrap inference developed in 'Roodman et al' (2019, 'STATA' Journal, <doi:10.1177/1536867X19830877>) and 'MacKinnon et al' (2022), which makes it feasible to quickly calculate bootstrap test statistics based on a large number of bootstrap draws even for large samples. Multiple bootstrap types as described in 'MacKinnon, Nielsen & Webb' (2022) are supported. Further, 'multiway' clustering, regression weights, bootstrap weights, fixed effects and 'subcluster' bootstrapping are supported. Further, both restricted ('WCR') and unrestricted ('WCU') bootstrap are supported. Methods are provided for a variety of fitted models, including 'lm()', 'feols()' (from package 'fixest') and 'felm()' (from package 'lfe'). Additionally implements a 'heteroskedasticity-robust' ('HC1') wild bootstrap. Last, the package provides an R binding to 'WildBootTests.jl', which provides additional speed gains and functionality, including the 'WRE' bootstrap for instrumental variable models (based on models of type 'ivreg()' from package 'ivreg') and hypotheses with q > 1.
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clustered-standard-errorslinear-regression-modelswild-bootstrapwild-cluster-bootstrapopenblascppopenmp
7.29 score 34 stars 2 dependents 317 scripts 105 downloadssummclust - Module to Compute Influence and Leverage Statistics for Regression Models with Clustered Errors
Module to compute cluster specific information for regression models with clustered errors, including leverage and influence statistics. Models of type 'lm' and 'fixest'(from the 'stats' and 'fixest' packages) are supported. 'summclust' implements similar features as the user-written 'summclust.ado' Stata module (MacKinnon, Nielsen & Webb, 2022; <arXiv:2205.03288v1>).
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clustered-standard-errorsfixestlinear-regressionrobust-inference
5.16 score 6 stars 3 dependents 54 scripts 62 downloadswildrwolf - Fast Computation of Romano-Wolf Corrected p-Values for Linear Regression Models
Fast Routines to Compute Romano-Wolf corrected p-Values (Romano and Wolf (2005a) <DOI:10.1198/016214504000000539>, Romano and Wolf (2005b) <DOI:10.1111/j.1468-0262.2005.00615.x>) for objects of type 'fixest' and 'fixest_multi' from the 'fixest' package via a wild (cluster) bootstrap.
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fixestmultiple-comparisonsromano-wolfwild-bootstrapwild-cluster-bootstrap
3.57 score 7 stars 1 dependents 35 scripts 12 downloadswithinr - High-Performance Fixed Effects Solver
Fast iterative solvers (CG, GMRES) with Schwarz domain-decomposition preconditioners for absorbing high-dimensional fixed effects in panel data regressions. The computational core is written in Rust via the 'within' crate and accessed through 'extendr'.
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rustcargo
3.13 score 9 stars